While smartphones have revolutionized the taking of images, in both content and quantity, the way those images are managed and organized has hardly kept pace. Users have collected thousands of moments and memories, yet these images are typically just saved to random, disorganized “albums” on smartphones, on social media or in cloud storage. This scattered and disorganized system has made it difficult to find and look back at old images. While images may be “tagged” with keywords in order to help identify images that include the same object, it may be difficult for a user to identify the images that include similar objects that are not tagged in the same manner. Further, while different techniques, such as Deep Learning, may be utilized as a classification tool, these techniques may not perform well as the number of words associated with a category grows. For example, as the semantics between words (or classes, used interchangeably below) starts to merge with each other, these different words or classes may overlap with one another. Thus, two different classes that are semantically similar, become more difficult and inefficient to classify, due to competition. As an example, the same object within an image that is at a slightly different angle or having a slightly different lighting condition may be recognized as a competing class. As such, the same object may be classified under two different classes.